Seiji Nishikage

Introduction The current clinical reality and burden of obesity disease in Japan are poorly understood. To address this knowledge gap, in this real-world study we describe the characteristics of Japanese individuals with obesity disease (IwOD) and their obesity disease treatments using data from the Japan Obesity Research Based on electronIc healTh record (J-ORBIT) database. Methods This retrospective observational study (January 2019 to January 2024) assessed data of ≥ 18-year-old IwOD registered in J-ORBIT and diagnosed with primary obesity per the criteria of the Japan Society for the Study of Obesity (JASSO). IwOD were grouped according to the most advanced treatment received during the study period, including the index date: lifestyle intervention, pharmacotherapy, or bariatric surgery. Demographic and clinical characteristics, degree of weight reduction, and percent change in metabolic parameters from baseline to the latest follow-up timepoint were described. Results Among the 782 IwOD included in this study, 274, 487, and 21 had received advanced treatment in the form of lifestyle intervention, pharmacotherapy, and bariatric surgery, respectively. At baseline, across treatment groups the mean age ranged from 45 to 57 years, female proportion ranged from 45% to 76%, and body mass index (BMI) ranged from 31 to 39 kg/m², respectively. Across treatment groups, 62–69% had ≥ 3 obesity-related health disorders (ORHDs) at baseline. Mean follow-up periods in these groups ranged from 846 to 1211 days. Mean weight and BMI numerically decreased from baseline to follow-up across groups. In the lifestyle intervention , pharmacotherapy, and bariatric surgery groups, 38%, 45%, and 65% of IwOD achieved ≥ 3% weight reduction at the latest follow-up timepoint. IwOD with baseline BMI ≥ 30 kg/ m² tended to achieve greater weight reduction. Triglyceride, high-density lipoprotein-cholesterol, blood glucose, hemoglobin A1c, and uric acid levels tended to improve in IwOD with ≥ 3% weight reduction and greater categories. Conclusion Obesity-associated burden in terms of ORHDs was common among Japanese IwOD. Although IwOD tended to have the highest weight reduction after bariatric surgery, this treatment is indicated for a highly restrictive population and requires specific criteria to be met, leaving many IwOD with unmet needs. These IwOD may need pharmacotherapy for better weight management than that provided by current options.

Background: Although several studies have evaluated the impact of prolonged infusion set use in insulin pump users on glycemic management with the use of continuous glucose monitoring (CGM), real-world assessments without intervention have been unavailable. Methods: This retrospective observational study recruited individuals with type 1 diabetes who received insulin pump therapy with real-time CGM. Insulin pump and CGM logs were extracted from the Medtronic CareLink system, and a dataset was constructed programmatically, counting tracking days from infusion set replacement every 24 hours up to day 4. The primary outcome was mean sensor glucose (SG) level, and the impact of infusion set usage duration on glycemic management was assessed. Results: The study enrolled 45 individuals with a median age of 40 (interquartile range = 32-51) years and median body mass index of 22.5 (21.2-23.8) kg/m². Mean SG was significantly higher on day 4 (median of 151.9 [136.5-173.7] mg/dL) than on day 2 (144.4 [124.0-162.9] mg/dL, P = .024). Similarly, time above range (TAR), time in range (TIR), and time in tight range (TITR) had worsened on day 4 compared with day 2. The TAR increased from a median of 22.0% (7.3%-35.8%) on day 2 to 27.6% (17.7%-44.9%) on day 4, whereas TIR decreased from 74.2% (59.9%-87.1%) to 66.5% (52.0%-79.8%) and TITR decreased from 47.6% (37.1%-67.5%) to 42.2% (34.6%-54.1%). Conclusions: Our evaluation of the real-world impact of prolonged infusion set use revealed an association between longer use and worsening of glycemic management.

Objective: Type A insulin resistance syndrome (IRS), characterized by impaired insulin receptor function due to variants of the insulin receptor gene, manifests as severe insulin-resistant diabetes. Differentiation of type A IRS from type 2 diabetes on the basis of hyperinsulinemia can be challenging. Given the association between insulin receptor dysfunction and reduced insulin clearance, we evaluated the potential of the circulating C-peptide reactivity (CPR)/immunoreactive insulin (IRI) molar ratio, a marker of insulin clearance, for distinguishing type A IRS from type 2 diabetes. Methods: We retrospectively analyzed CPR and IRI levels measured during a 75-g oral glucose tolerance test (OGTT) in 18 individuals with type A IRS and 126 with type 2 diabetes. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic performance of the CPR/IRI molar ratio and IRI levels. Results: IRI levels were significantly higher and the CPR/IRI molar ratio significantly lower in individuals with type A IRS compared with those with type 2 diabetes. The area under the ROC curve for the CPR/IRI molar ratio at baseline, 1 hour, and 2 hours after OGTT initiation was 0.997 (sensitivity 100%, specificity 99.2%), 0.999 (sensitivity 100%, specificity 97.6%), and 0.997 (sensitivity 100%, specificity 95.1%), respectively. The CPR/IRI molar ratio demonstrated robust diagnostic performance regardless of body mass index or hyperinsulinemia severity. Conclusion: The CPR/IRI molar ratio, both at baseline and during OGTT, exhibited higher sensitivity and specificity than IRI levels alone for distinguishing type A IRS from type 2 diabetes. This ratio may serve as a reliable clinical marker for early and accurate diagnosis of type A IRS.

The use of asfotase alfa, a bone-targeted recombinant alkaline phosphatase (ALP) enzyme, for the treatment of adult-onset hypophosphatasia (HPP) remains controversial, particularly in patients without evident bone abnormalities. We report the case of a 41-year-old woman with a history of Graves’ disease, who presented with progressive joint pain and severe fatigue. Despite the absence of bone lesions, the patient was diagnosed with HPP based on persistently low alkaline phosphatase levels, family history, and a novel heterozygous ALPL variant (p.Ala205Thr). Functional analysis revealed a dominant-negative effect for this variant. Her symptoms significantly interfered with her daily activities owing to uncontrolled pain and loss of motor function and were so exacerbated that high doses of acetaminophen and NSAIDs were ineffective. Treatment with asfotase alfa was initiated based on multidisciplinary team consensus. Within 3 months of treatment initiation, her pain improved significantly, as indicated by reduced scores on the visual analog scale from 6.6 to 0.9, and elimination of the need for analgesics. Additionally, her grip strength increased, and her urinary phosphoethanolamine levels and serum pyridoxal 5'-phosphate/pyridoxal ratio decreased from 90.4 to 57.8 μmol/g·creatinine and from 4.6 to 0.4, respectively. These improvements have been maintained for more than 2 years. This case highlights the potential of asfotase alfa in effectively alleviating symptoms in patients with adult-onset HPP without bone lesions, emphasizing the importance of patient selection and outcome monitoring. We also discuss the key considerations for future treatment, supported by a literature review of asfotase alfa in adult patients with HPP.

Context: Adverse events related to insulin therapy remain common in individuals with type 1 diabetes (T1D). Optimization of insulin dose can reduce the frequency of these events and help to prevent macrovascular and microvascular complications. Objective: The aim of the present study was to develop machine-learning models to predict the total daily dose (TDD) of insulin on the basis of data available in routine clinical practice, to evaluate the performance of the models, and to interpret the relation between its predictions and features. Methods: This retrospective observational study conducted at a single center recruited individuals diagnosed with T1D who visited Kobe University Hospital and used continuous glucose monitoring in combination with continuous subcutaneous insulin infusion between April 1, 2010 and February 29, 2024. We developed TDD prediction models based on machine learning and evaluated its performance on the basis of the mean absolute percentage error (MAPE). Explainable artificial intelligence frameworks were applied to the machine-learning model to facilitate interpretability. Results: A total of 110 individuals with T1D were included in the study. The best-performing model, the random forest, achieved a MAPE of 19.8%. The most important feature of the model for prediction of the TDD of insulin was body weight, followed by waist circumference and carbohydrate intake. Conclusion: We here developed machine-learning models that predict the TDD of insulin from clinical information. Such models could contribute to the treatment of many individuals undergoing insulin therapy, with further developments being warranted.